During filling of a liquid container onboard a vehicle, such as a fuel tank onboard an aircraft, and during subsequent movement of the vehicle, build-up, transport, and relaxation of electrostatic charge in the liquid container may result in undesirable conditions within the liquid container. Such conditions are increased especially during the transfer of liquid into the liquid container. For example, a filter provided in the liquid container interacts with the incoming liquid such that the electric charge is stripped from the liquid and bulk polarization of the liquid is caused. Such charged liquid being transferred into the liquid container is able to interact with the surrounding environment of the container, where if enough electric potential builds up, electric arcing may occur. Risks including loss of functionality of the liquid container, electrical vulnerabilities of the liquid container, and the like are a logical by-product of the undesirable conditions that may result from the electrostatic charge build-up, transport, and relaxation.
In order to mitigate these risks, analysis teams use experimentation tools to understand and predict the risks. The teams may use this information to optimize the design of the liquid container and to certify that requirements for reliability and risk tolerance are met.
The design and certification of a liquid container, and any associated components, can be expensive and laborious. Current certification processes do not provide sufficient feedback to designers of the liquid container to understand the physical conditions and risks that the liquid container will be subjected to and to sufficiently improve the design and implementation accordingly. Shortcomings of the current processes include the absence of: genuine boundary conditions, electrostatic charge transport models, isolated conductors, fluid dynamics, which result in various generalizations and assumptions as to the liquid container's geometry, an inlet charge density, conductivity of the liquid, and liquid flow rate and, thus, lower-fidelity numerical predictive models than may be desirable.
Therefore it would be desirable to have an apparatus and method that takes into account at least some of the issues discussed above, as well as other possible issues.